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检索条件"主题词=Mixed integer linear programming"

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Formulations and algorithms for the multiple depot, fuel-constrained, multiple vehicle routing problem

Formulations and algorithms for the multiple depot, fuel-con...

引用

American Control Conference

作者： Kaarthik Sundar Saravanan Venkatachalam Sivakumar Rathinam Dept. of Mechanical Engg. Texas A&M University College Station 77843 USA Dept. of Industrial and Systems Engg. Wayne State University Detroit MI 48202 USA

ISBN: (纸本)9781467386838

We consider a multiple depot, multiple vehicle routing problem with fuel constraints. We are given a set of targets, a set of depots and a set of homogeneous vehicles, one for each depot. The depots are also allowed to act as refueling stations. The vehicles are allowed to refuel at any depot, and our objective is to determine a route for each vehicle with a minimum total cost such that each target is visited at least once by some vehicle, and the vehicles never run out fuel as it traverses its route. We refer to this problem as the Multiple Depot, Fuel-Constrained, Multiple Vehicle Routing Problem (FCMVRP). This paper presents four new mixed integer linear programming formulations to compute an optimal solution for the problem. Extensive computational results for a large set of instances are also presented.

关键词： unmanned vehicle routing fuel constraints green vehicle routing electric vehicles mixed-integer linear programming WAREHOUSE vehicle Electric vehicles mixed integer linear programming Vehicle routing Total Costs Refuelling

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On Evaluation of Onsite Energy Storage for Various End-Use Facilities with Utility Bill Management, Arbitrage, and Frequency Regulation Opportunities

On Evaluation of Onsite Energy Storage for Various End-Use F...

引用

Innovative Smart Grid Technologies (ISGT)

作者： Farhad Angizeh Ali Ghofrani Esmat Zaidan Mohsen A. Jafari Rutgers The State University of New Jersey Piscataway NJ USA College of Arts and Sciences Qatar University Doha Qatar

ISBN: (数字)9781728188973

ISBN: (纸本)9781728188980

This paper proposes a comprehensive evaluating framework that enables facility operators to optimally size and dispatch their onsite energy storage systems (ESS) that might be operated as either standalone or integrated solar-plus-storage systems. The proposed model is developed on an energy procurement-based model with a mixed-integer linear programming (MILP) format, wherein the potential energy and demand charge savings though utility bill management (UBM) and revenue streams from energy arbitrage and frequency regulation (FR) opportunities are co-optimized. PJM's pay-for-performance regulation market is considered to remunerate the facility's dedicated capacities to the FR market. To investigate the impacts of facility behavior on the evaluation of various onsite ESSs, a set of 24 facilities from different end-use sectors with different functionalities are simulated. The practicality of the proposed evaluation model is then investigated through two case studies where the impacts of various optimally-operated onsite ESSs on maximizing the potential benefits are quantified.

关键词： Potential energy Simulation Regulation Smart grids mixed integer linear programming Frequency control Energy storage

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Optimization and Research on Army Vehicle Deployment in Emergency Situations

Optimization and Research on Army Vehicle Deployment in Emer...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Haoran He Xiaoxiong Zhang Jun Yang Xiaolei Zhou Hao Yan Sixty-third Research Institute National University of Defense Technology Nanjing China School of Electronics and Information Engineering Nanjing University of Information Science and Technology Nanjing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In the event of disasters, emergencies, or special circumstances, the military needs to deploy vehicle resources to meet the needs of emergency response and rescue work. This problem involves the reasonable allocation and utilization of limited vehicle resources to complete emergency tasks quickly and efficiently while reducing casualties and property losses. However, there are still some difficulties regarding the military vehicle deployment problem, including uneven resource deployment, low deployment efficiency, and insufficient logistics protection. Herein, a mixed-integer linear programming model is constructed to optimize the deployment problem of military vehicles to minimize the total transportation time and cost. Considering the complexity and uncertainty in military operations, this paper introduces a variety of constraints, particularly in terms of vehicle number, geographical limitation, and strategic vehicle. With the designed model, instances of problems of different scales are solved, and comparisons are drawn with the existing deployment methods. The results show that the proposed model can effectively reduce the time and cost required for vehicle deployment, while significantly improving the flexibility and adaptability of the deployment scheme. This study can not only provide a new optimization tool for army vehicle deployment but also be utilized for other similar types of emergency logistics deployment.

关键词： Adaptation models Costs Accuracy Uncertainty Optimization models Transportation Military vehicles mixed integer linear programming Optimization Logistics

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DyPro: Dynamic Probing Planning for In-Band Network Telemetry

DyPro: Dynamic Probing Planning for In-Band Network Telemetr...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Leandro M. Dallanora Ariel G. Castro Roberto I. T. da Costa Filho Fabio D. Rossi Arthur F. Lorenzon Marcelo C. Luizelli Federal University of Pampa (UNIPAMPA) Federal Institute Sul-Rio-Grandense (IFSul) Federal Institute Farroupilha (IFFAR)

ISBN: (数字)9781665497923

ISBN: (纸本)9781665497930

In-band Network Telemetry (INT) is a novel net-work monitoring mechanism that improves fine-grained net-work visibility. Despite the increasing research efforts towards the orchestration of INT data acquisition, little has yet been done to efficiently collect telemetry data from the network considering monitoring applications requirements. In this paper, we introduce DyPro - a dynamic probing planning for INT. In particular, DyP ro ensures that telemetry dependencies are always satisfied by monitoring application requirements. We theoretically formalize it as a mixed-integer linear programming (MILP) optimization model and propose a heuristic procedure to efficiently solve it. Results show that DyP ro can outperform state-of-the-art solutions by up to 5x regarding the percentage of monitoring applications satisfied.

关键词： Computers Computational modeling Data acquisition Planning mixed integer linear programming Telemetry Monitoring

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Proposition of a Portfolio optimization System to Manage a Commercial Virtual Power Plant in the Brazilian Free Energy Market

Proposition of a Portfolio optimization System to Manage a C...

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IEEE International Energy Conference and Exhibition (EnergyCon)

作者： Carlos José Alves Santos Isla Almeida Oliveira Pâ mela Rugoni Belin Mathias Arno Ludwig Jú lia Da Rosa H. Rodrigues Marcos Auré lio I. Martins Sustainable Energy Center CERTI Foundation Florian&#x00F3 polis Brazil R&#x0026 D and Innovation AES Brasil S&#x00E3 o Paulo Brazil

In face of the possibility of freely trading energy in the Brazilian market, a model is proposed to define an optimal contracting strategy for a Commercial Virtual Power Planet (CVPP) for years ahead. The idea behind the CVPP is to aggregate loads in order to obtain contractual benefits, acquiring long-term contracts at lowest prices and taking advantage of the complementary nature of the load profiles when settling the differences between consumption and contracts. The model, called Portfolio optimization System (POS) – in Portuguese, “Sistema de Otimização de Portfólio” (SOP) –, is based on mixed-integer linear programming (MILP) and aims to maximize profit, considering a certain level of risk, represented by the Conditional Value-at-Risk (CVaR). In this paper the motivation behind the model and its potential market value as a tool for portfolio management, especially for energy retailers, are presented. With the Brazilian Energy Market business rules defined, a case study is proposed in order to compare optimized long-term contracting and short-term contracting without any optimization. The profit resulting from the use of the tool is valued at 31% in this case study.

关键词： Planets Aggregates Virtual power plants mixed integer linear programming Portfolios Optimization Contracts

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An unconventional clustering problem: User Service Profile Optimization

An unconventional clustering problem: User Service Profile O...

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IEEE International Symposium on Information Theory

作者： Fabio D'Andreagiovanni Giuseppe Caire Dept. of Mathematical Optimization CNR Italy Chair of Communications and Information Theory Technische Universität Berlin Germany

ISBN: (纸本)9781509018079

We consider the problem of clustering N users into K groups such that users in the same group are assigned a common service profile over M commodities. The profile of each group k sets for each commodity m the maximum of the service quality that users in the k-th group are willing to pay. The objective is to find the clustering that maximizes the total service user quality, which corresponds to the revenue of the service provider. This Service Profile Optimization Problem (SPOP) emerges in various applications, as for example the bit-loading in Hybrid Fiber Coax data distribution systems. We propose a mixed integer linear programming (MILP) model for the problem, that allows to use state-of-the-art MILP solvers as the core tool in an original powerful heuristic. We show complexity and performance gains with respect to previously proposed methods and a direct application of a state of the art MILP solver.

关键词： Optimization linear programming Information theory Hybrid fiber coaxial cables OFDM Clustering algorithms mixed integer linear programming

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Energy Management for Prepaid Customers: A linear Optimization Approach

Energy Management for Prepaid Customers: A Linear Optimizati...

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IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Maitreyee Marathe Line A. Roald Dept. of Electrical and Computer Engineering University of Wisconsin-Madison Madison USA

ISBN: (数字)9798350318555

ISBN: (纸本)9798350318562

With increasing energy prices, low income households are known to forego or minimize the use of electricity to save on energy costs. If a household is on a prepaid electricity program, it can be automatically and immediately disconnected from service if there is no balance in its prepaid account. Such households need to actively ration the amount of energy they use by deciding which appliances to use and for how long. We present a tool that helps households extend the availability of their critical appliances by limiting the use of discretionary ones, and prevent disconnections. The proposed method is based on a linear optimization problem that only uses average power demand as an input and can be solved to optimality using a simple greedy approach. We compare the model with two mixed-integer linear programming models that require more detailed demand forecasts and optimization solvers for implementation. In a numerical case study based on real household data, we assess the performance of the different models under different accuracy and granularity of demand forecasts. Our results show that our proposed linear model is much simpler to implement, while providing similar performance under realistic circumstances.

关键词： Home appliances Uncertainty Computational modeling Electricity Predictive models Numerical models mixed integer linear programming Smart grids Optimization Load modeling

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Module selection and scheduling using unrestricted libraries

Module selection and scheduling using unrestricted libraries

引用

European Conference on Design Automation

作者： A.H. Timmer M.J.M. Heijligers L. Stok J.A.G. Jess Department of Electrical Engineering Design Automation Section Eindhovan University of Technology Eindhoven Netherlands IBM Thomas J. Watson Research Center Yorktown Heights NY USA

Most high-level synthesis schedulers are capable only of mapping an operation to one specific module type. To ensure a full design space exploration, a synthesis system should however select freely from a library containing modules with a large variety in delay, area and so on. A module selection and scheduling approach which allows the full use of such unrestricted libraries is presented. Extensive benchmark results show very fast running times and optimal solutions. This approach clearly illustrates the advantages of synthesis tools which can fully cope with unrestricted libraries, as they lead to designs with less module area.< >

关键词： Libraries Space exploration Delay High level synthesis Space technology Design automation Flow graphs Hardware mixed integer linear programming Scheduling algorithm

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Reactive re-provisioning heuristics for mitigating the impact of traffic pattern variations on multi-layer optical networks

Reactive re-provisioning heuristics for mitigating the impac...

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International Conference on Photonics in Switching (PS)

作者： N. Andriolli L. Valcarenghi P. Castoldi Scuola Superiore Sant'Anna Pisa Italy

This study presents an evaluation of heuristics that reconfigure a multi-layer network logical topology for efficiently accommodating variable traffic patterns. Numerical results show that reconfiguration is useful if... 详细信息

关键词： Telecommunication traffic Optical fiber networks Network topology Traffic control Fluctuations Convergence Routing Resource management mixed integer linear programming Europe

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Unit Commitment and Optimal Power Flow Based Optimal Sizing Strategy of Energy Storage Systems

Unit Commitment and Optimal Power Flow Based Optimal Sizing ...

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International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE)

作者： Mohammed A. Abdulgalil Megat Gadalla Kamal Ramadan Doud

This paper proposes a new strategy to optimally size an energy storage system (ESS) based on optimization problems in power systems. These optimization problems are unit commitment (UC) which is solved using mixed-integer linear programming (MILP), DC optimal power flow (DC-OPF) which is solved using linear programming (LP), and AC optimal power flow (AC-OPF) which is solved using non-linear programming (NLP). The proposed strategy is tested on the IEEE Reliability Test System (RTS-96) 24-bus system. The results show the effectiveness of integrating an ESS to a power system, which is a microgrid in this paper. General algebraic modeling system (GAMS) is used to model and solve the proposed models.

关键词： Microgrids programming linear programming Power system reliability Planning mixed integer linear programming Reliability

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